Experience

AI/ML and cloud engineering professional with experience building enterprise-grade data platforms, backend systems, and intelligent applications. Currently an AI/ML Engineer at MiniMed, with expertise in Python, Generative AI, AWS, data engineering, APIs, automation, and cloud-native solutions. I focus on delivering scalable, reliable systems that solve business problems while maintaining engineering excellence, security, and performance.

Experience

Medtronic - Senior AI/ML Engineer

- Present

Led cloud data engineering initiatives at Medtronic, building and optimizing large-scale data pipelines on AWS for healthcare analytics and AI-driven insights while maintaining strict compliance with healthcare data governance and security standards.
  • Built and optimized Python and Apache Spark (AWS Glue) pipelines on AWS for large-scale data processing, analytics, and ML workflows handling petabytes of healthcare data.
  • Integrated Amazon Bedrock into data and AI workflows, enabling secure LLM-based classification, enrichment, and summarization with IAM-based access control and compliance guardrails.
  • Designed and executed SageMaker pipelines for ML inference and data enrichment, integrating model outputs back into analytical data stores for real-time decision support.
  • Implemented secure IAM roles and least-privilege policies for Glue, Lambda, Redshift, and Bedrock, ensuring compliance with enterprise security and healthcare data governance standards (HIPAA).
  • Collaborated with analytics, ML, and platform teams to deliver end-to-end data solutions, from ingestion through AI-driven insights, reporting, and operational dashboards.
  • Built serverless automation and monitoring solutions using AWS Lambda, EventBridge, and CloudWatch to track pipeline health, data freshness, and operational SLAs.
  • Implemented secure credential management using IAM roles and AWS Secrets Manager, eliminating hard-coded secrets and improving security posture across serverless applications.
  • Created and managed comprehensive IAM roles and least-privilege policies for Lambda, Glue, Redshift, and Bedrock, ensuring secure access to PHI-sensitive healthcare data.

Fannie Mae - AWS Engineer

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Developed and managed AWS cloud infrastructure automation and governance solutions at Fannie Mae, enabling seamless provisioning and management of cloud services across the organization while maintaining security and compliance standards.
  • Developed and distributed automated infrastructure-as-code processes for building AWS cloud infrastructure across the organization, reducing deployment time by 60%.
  • Designed and managed enterprise IAM service enabling application teams to create, manage, and audit AWS IAM roles and policies without manual intervention.
  • Built AWS Service Catalog products for automated provisioning of EC2, RDS, Elastic Beanstalk, and other AWS services, eliminating the need for custom CloudFormation templates.
  • Written Python scripts and Lambda functions for day-to-day monitoring, alerting, and automation activities across AWS infrastructure using Boto3 and AWS CLI.
  • Configured AWS CodeCommit, CodePipeline, and CloudFormation for CI/CD deployment of Lambdas, CloudWatch alarms, SNS, and SQS resources at scale.
  • Implemented comprehensive security controls and access management strategies for AWS resources across multiple accounts and business units.
  • Automated compliance reporting and audit trails for IAM role usage and permission changes across the organization.
  • Mentored junior engineers on AWS best practices, infrastructure automation, and cloud security principles.

Vanguard Group - Hadoop Developer

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Engineered and deployed large-scale data lake infrastructure on AWS for Vanguard Group, implementing end-to-end data ingestion pipelines and processing millions of records daily using modern big data technologies and cloud services.
  • Built and deployed Data Lake in AWS cloud, designing end-to-end data ingestion pipeline to transfer on-premises data to cloud under Agile/Scrum methodology.
  • Leveraged AWS services including EMR, Lambda, SQS, Kinesis Streams, Secrets Manager, CloudWatch, CloudFormation, EC2, and S3 for scalable data processing.
  • Migrated millions of records using Attunity to Kinesis Streams, processing through Python Lambda functions with robust error handling and cross-account role assumptions.
  • Implemented SQS as on-failure destination for Kinesis Lambda functions, ensuring reliable error handling and retry mechanisms across distributed data pipelines.
  • Optimized handling of large data sets using partitioning, Apache Spark in-memory capabilities, efficient joins, and transformations during ingestion and processing.
  • Developed shell scripts and Python automation workflows for data ingestion orchestration, generating JSON Oozie workflows dynamically.
  • Used Troposphere in Python to auto-generate CloudFormation templates in JSON format, enabling Infrastructure-as-Code deployment of big data environments.
  • Worked with multiple file formats (TEXTFILE, SEQUENCE, AVRO, ORC, PARQUET) for Hive querying, optimizing storage and query performance.

Veritis Group Inc. - Java/Hadoop Developer

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Developed data engineering and big data solutions at Veritis Group, implementing Hadoop-based data pipelines, stream processing, and database transformations for enterprise data integration and analytics platforms.
  • Ingested files to HDFS using Java Kafka publisher and consumer APIs for streaming applications, handling high-volume data ingestion with fault tolerance.
  • Utilized HDFS Java API to put and retrieve files from HDFS, implementing efficient data movement and storage strategies.
  • Implemented comprehensive Cucumber test cases to compare and validate data before and after transformations, ensuring data quality and integrity.
  • Used Apache Pig for ETL transformations, event joins, filters, and pre-aggregations before storing data into HDFS for downstream analytics.
  • Created and managed external and internal Hive tables with proper partitioning strategies and optimized data storage formats for query performance.
  • Worked on Hibernate framework to implement ORM-based insert, update, and delete operations in MySQL Database with proper transaction management.
  • Used Log4j for comprehensive logging across applications, writing audit logs to files for compliance, monitoring, and troubleshooting purposes.
  • Written shell scripts for file automation processes, scheduling, and orchestration of recurring data pipeline jobs.

Education

Skills

Languages & Automation

Boto3PythonSQLAWS CLIShell Scripting

Enterprise AI & Generative AI

Amazon BedrockLLM WorkflowsPrompt EngineeringSageMakerModel EvaluationRAGResponsible AI

AWS & Cloud

AWS GlueIAMLambdaRedshiftS3CloudFormationCloudWatchDataZoneEventBridgeStep Functions

Data Engineering

Apache SparkData LakesETL/ELTPandasPySparkHadoopHiveKafka

Databases

Amazon RedshiftDB2DynamoDBMySQLPostgreSQL

DevOps, Security & Observability

GitIAM GovernanceSecrets ManagerCI/CDJenkinsSplunk

References available upon request. Get in touch →